Validity vs. Correctness Continued: Accuracy Percentages
Filed under: Business Impacts, Data Quality, Identity Resolution, Master Data
Yesterday I shared some thoughts about the differences between data validity and data correctness, and why validity is a good start but ultimately is not the right measure for quality. Today I am still ruminating about what data correctness or accuracy really means.
For example, I have been thinking for a long time about the existence (or more accurately, nonexistence) of benchmarks for data quality methods and tools, especially when it comes to data accuracy. On the one hand, I often see both vendors and their customers reporting “accuracy percentages” (e.g. “our customer data is 99% accurate”) and I wonder what is meant by accuracy and how those percentages are both calculated and verified.
The Validity of Value Validation
I have nothing against data validation as a general practice. In fact, I might claim to be one of the more forceful proponents of validation as a practical methodology, having written a book that has guided the development of automated data validation tools. Yet validation only provides one level of trust when it comes to evaluating the quality of information. Read more